263794 Automation and Control of Drug-On-Demand Technology

Wednesday, October 31, 2012: 5:20 PM
Allegheny II (Westin )
Laura Hirshfield, Arun Giridhar, Gintaras V. Reklaitis, Michael T. Harris and Venkat Venkatasubramanian, Chemical Engineering, Purdue University, West Lafayette, IN

Stimulated by initiatives such as PAT and QbD, the pharmaceutical industry has been focusing on the development of innovative, efficient manufacturing methods. The concept of "mini-manufacturing" of drugs, as opposed to mass production of drugs, has shown promise in this area. We describe one such mini-manufacturing process, "drug-on-demand," which uses drop-on-demand printhead technology to deposit active pharmaceutical ingredients (API) onto edible substrates. We use a high precision positive displacement pump to deposit polymer-drug melts. Besides minimizing a need for mass production of all drugs, this method allows for the layering of different APIs and the creation of individual dosing forms, in which the amount of API can be varied depending on the patient.

In this work, we focus on the automation, control and Exceptional Events Management (EEM) strategy for the drug-on-demand pilot facility done as part of the Engineering Research Center for Structured Organic Particulate Systems. A proper control strategy is necessary so that the system can run at optimal setpoints and adjust in real-time, allowing for an efficient manufacturing process and a precise on-specification drug product. The control strategy for our “drug-on-demand” setup allows us to execute an automated, optimized, and controlled print cycle while closely monitoring drop size, drug morphology, and drop deposition pattern. The implementation of EEM allows for detection, diagnosis, and mitigation of abnormal events that occur outside of the control space to ensure a more efficient, productive process. In this session, we summarize our achievements and current research in this area.

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